TY - GEN
T1 - Syntax aware lstm model for semantic role labeling
AU - Qian, Feng
AU - Sha, Lei
AU - Chang, Baobao
AU - Liu, Lu Chen
AU - Zhang, Ming
N1 - Publisher Copyright:
© EMNLP 2017.All right reserved.
PY - 2017
Y1 - 2017
N2 - In Semantic Role Labeling (SRL) task, the tree structured dependency relation is rich in syntax information, but it is not well handled by existing models. In this paper, we propose Syntax Aware Long Short Time Memory (SA-LSTM). The structure of SA-LSTM changes according to dependency structure of each sentence, so that SA-LSTM can model the whole tree structure of dependency relation in an architecture engineering way. Experiments demonstrate that on Chinese Proposition Bank (CPB) 1.0, SA-LSTM improves F1 by 2.06% than ordinary bi-LSTM with feature engineered dependency relation information, and gives state-of-the-art F1 of 79.92%. On English CoNLL 2005 dataset, SA-LSTM brings improvement (2.1%) to bi-LSTM model and also brings slight improvement (0.3%) when added to the stateof- the-art model.
AB - In Semantic Role Labeling (SRL) task, the tree structured dependency relation is rich in syntax information, but it is not well handled by existing models. In this paper, we propose Syntax Aware Long Short Time Memory (SA-LSTM). The structure of SA-LSTM changes according to dependency structure of each sentence, so that SA-LSTM can model the whole tree structure of dependency relation in an architecture engineering way. Experiments demonstrate that on Chinese Proposition Bank (CPB) 1.0, SA-LSTM improves F1 by 2.06% than ordinary bi-LSTM with feature engineered dependency relation information, and gives state-of-the-art F1 of 79.92%. On English CoNLL 2005 dataset, SA-LSTM brings improvement (2.1%) to bi-LSTM model and also brings slight improvement (0.3%) when added to the stateof- the-art model.
UR - https://www.scopus.com/pages/publications/85121115602
M3 - 会议稿件
AN - SCOPUS:85121115602
T3 - EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the 2nd Workshop on Structured Prediction
SP - 27
EP - 32
BT - EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the 2nd Workshop on Structured Prediction
PB - Association for Computational Linguistics (ACL)
T2 - 2nd Workshop on Structured Prediction for Natural Language Processing, SPNLP 2017, held in conjunction with the Conference on Empirical Methods in Natural Language Processing, EMNLP 2017
Y2 - 9 September 2017 through 11 September 2017
ER -